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  3. A scientometrics survey on project scheduling

A scientometrics survey on project scheduling

This paper presents a comprehensive review of the studies associated with project scheduling. The study uses Sco-pus database as a primary search engine and covers 3370 records over the period 1963-2019. Journal of Project Management 4 (2019) 165–176 Contents lists available at GrowingScience Journal of Project Management homepage: www.GrowingScience.com A scientometrics survey on project scheduling M. R. Ghaelia* and Soheil Sadi-Nezhadb a Department of Commerce and Business Administration, New

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  1. Journal of Project Management 4 (2019) 165–176 Contents lists available at GrowingScience Journal of Project Management homepage: www.GrowingScience.com A scientometrics survey on project scheduling M. R. Ghaelia* and Soheil Sadi-Nezhadb a Department of Commerce and Business Administration, New Westminster, BC, Canada b Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Canada CHRONICLE ABSTRACT Article history: In project management, a schedule is considered as a list a project's milestones, activities, Received: October 28 2018 and deliverables, normally with some start and finish time schedule, which are estimated by Received in revised format: No- some information incorporated in the project schedule including resource allocation, budget, vember 25 2018 task duration, and linkages of dependencies and scheduled events. This paper presents a Accepted: January 23 2019 Available online: comprehensive review of the studies associated with project scheduling. The study uses Sco- January 23 2019 pus database as a primary search engine and covers 3370 records over the period 1963-2019. Keywords: The records are statistically analyzed and categorized in terms of different criteria. Based on Project scheduling the survey, "decision support systems" is the keyword which has carried the highest densities Highly cited followed by heuristics methods. Among the most cited articles, papers published by re- Country searchers in Germany have received the highest citations (9084), followed by United States Scientometrics (7058) and Belgium with 4853 citations. © 2019 by the authors; licensee Growing Science, Canada. 1. Introduction In project management, a schedule is considered as list a project's milestones, activities, and deliv- erables, normally with some start and finish time schedule, which are estimated by some infor- mation incorporated in the project schedule including resource allocation, budget, task duration, and linkages of dependencies and scheduled events. Any schedule is normally implemented in the project planning and project portfolio management as parts of project management. Elements on a schedule are associated with different issues such as the work breakdown structure (WBS) terminal elements, the statement of work, etc. Project scheduling has been used in the literature for years (Krauss, 1963; Moshman et al., 1963; Betzig, 1964). The object of project scheduling and manage- ment is to produce a complete project by considering the client's desires. In several cases, the pri- mary object of project management is to change the client's brief to address the client's objectives. When the client's targets become transparent, they ought to influence all decisions made by other parties involved in the project such as project managers, designers, contractors, etc. This paper pre- sents an overview on studies associated with project scheduling. The study uses Scopus database as a primary search engine and analyzes the data over the period 1963-2019. * Corresponding author. E-mail address: rghaeli@nyit.edu (M. R. Ghaeli) © 2019 by the authors; licensee Growing Science, Canada doi: 10.5267/j.jpm.2019.1.006          
  2. 166   2. The most common keywords Table 1 demonstrates some of the mostly cited references associated with project scheduling. As we can observe from the results of Table 1, Scheduling, Project scheduling and Project management are three well recognized keywords used in the literature. Fig. 1 shows the most important words used over times. Table 1 The most popular keywords used in studies associated with project scheduling Terms Frequency Terms Frequency scheduling 1210 activity duration 50 project scheduling 674 combinatorial optimization 49 project management 446 makespan 48 optimization 394 project duration 48 problem solving 319 computer software 47 algorithms 316 critical path analysis 47 resource-constrained project scheduling problem 298 iterative methods 46 genetic algorithms 258 precedence constraints 45 resource allocation 241 tabu search 44 heuristic methods 236 uncertainty analysis 44 constraint theory 194 random processes 43 scheduling algorithms 182 production control 42 mathematical models 171 decision support systems 40 project scheduling problem 167 priority rules 40 resource constrained project scheduling 156 resource constraints 40 costs 128 local search 39 integer programming 122 mathematical programming 38 heuristic algorithms 100 resource-constrained project scheduling 37 constrained optimization 99 construction management 36 decision making 99 critical chain 36 computational complexity 93 rcpsp 36 construction industry 92 managers 35 artificial intelligence 91 production engineering 35 resource constraint 84 strategic planning 35 evolutionary algorithms 83 heuristics 34 operations research 82 construction 33 resource-constrained 82 critical path method 32 computer simulation 81 economic and social effects 32 computational results 80 precedence relations 32 multi-project scheduling 79 project activities 32 construction projects 76 heuristic programming 31 computational experiment 74 software engineering 31 benchmarking 66 dynamic programming 30 particle swarm optimization (pso) 63 flow measurement 30 scheduling problem 63 industrial engineering 30 computer programming 62 product development 30 simulated annealing 62 constraint programming 29 multiobjective optimization 61 graph theory 29 linear programming 60 meta heuristics 29 stochastic systems 59 np-hard 29 fuzzy sets 58 objective functions 29 computational methods 57 optimization problems 29 pert 57 multi agent systems 28 multi-mode resource-constrained project scheduling problem 54 project managers 28 net present value 54 project planning 28 multimodes 52 uncertainty 28 planning 52 optimal solutions 27
  3. M. R. Ghaeli and S. Sadi-Nezhad / Journal of Project Management 4 (2019) 167 3. Contributions of countries Our survey demonstrates that European countries have maintained the most contribution in the field of project scheduling. Table 2 shows details of our survey. Table 2 The summary of the contributions of different countries Country Total Citations Average Article Citations GERMANY 9084 63.52 USA 7058 29.05 BELGIUM 4853 55.15 CHINA 2816 10.71 SPAIN 1919 35.54 IRAN 1829 15.12 FRANCE 1618 24.15 POLAND 1348 18.99 TURKEY 1110 27.75 TAIWAN 1100 21.57 CANADA 1070 23.26 UNITED KINGDOM 794 30.54 ITALY 723 21.26 INDIA 682 14.51 HONG KONG 667 37.06 AUSTRALIA 646 16.56 JAPAN 637 19.91 ISRAEL 513 21.38 KOREA 460 21.90 GREECE 448 23.58 SINGAPORE 437 23.00 PORTUGAL 262 18.71 THAILAND 246 22.36 AUSTRIA 232 23.20 BRAZIL 232 15.47 SOUTH AFRICA 190 95.00 CZECH REPUBLIC 176 22.00 TUNISIA 172 17.20 NETHERLANDS 167 12.85 LEBANON 163 81.50 SAUDI ARABIA 149 37.25 HUNGARY 138 9.20 COLOMBIA 119 17.00 QATAR 109 54.50 SWITZERLAND 108 12.00 CHILE 84 9.33 ARMENIA 80 40.00 ARGENTINA 69 17.25 EGYPT 66 9.43 NEW ZEALAND 56 11.20 MALAYSIA 45 9.00 NORWAY 44 14.67 SWEDEN 38 38.00 NIGERIA 29 7.25 CYPRUS 28 5.60 FINLAND 19 9.50 SLOVENIA 17 5.67 CAMEROON 14 4.67 DENMARK 14 14.00 LITHUANIA 11 5.50 IRELAND 10 5.00 BELARUS 9 9.00 CROATIA 9 2.25 MEXICO 8 8.00 PAKISTAN 7 3.50 LUXEMBOURG 6 6.00 INDONESIA 2 2.00 KUWAIT 2 2.00 VENEZUELA 2 2.00
  4. 168   Fig. 1. The summary of the most popular keywords used in project scheduling According to Table 2, researchers from Germany have published 9084 papers followed by United States with 7058 papers and Belgium with 4853 papers. In terms of the average citation, papers published by researchers in Germany and Belgium have maintained the highest citations. Fig. 3 shows the results of the collaborations among various countries. Fig. 3. Country collaboration map
  5. M. R. Ghaeli and S. Sadi-Nezhad / Journal of Project Management 4 (2019) 169 As we can observe from the results of Fig. 3, there were strong collaboration from the researchers in United States from one side and other countries. 4. Highly cited papers Table 3 shows the summary of the most cited articles. As we can observe from the results of Table 3, the study by Brucker et al. (1999) has received the highest citations. In their study, they provided a classification scheme, i.e. an explanation for the resource environment, the activity characteristics, and the objective function, respectively, which is consistent with machine scheduling and helps classify the most important models. They also proposed a unifying notation to review some of the recent developments such as exact and heuristic algorithms for the single-mode and the multi-mode case, for the time–cost tradeoff problem, etc. The second highly cited work is associated with Kolisch and Drexl (1997) where they provided a local search for non-preemptive multi-mode re- source-constrained project scheduling. They proposed a general class of non-preemptive resource- constrained project scheduling problems where activity durations were discrete functions of com- mitted renewable and nonrenewable resources. They obtained a 0-1 problem formulation and ex- plained the model by applying applications within production and operations management. In ad- dition, they proved that the feasibility problem which is NP-complete and could hardly deal with some shortcomings. Thus, they proposed a new local search method that initially attempt to locate a feasible solution and then executed a single-neighborhood search on the set of feasible mode assignments. They also performed a computational study on two benchmark sets where the experi- ment included a comparison of the procedure with other heuristics. The third highly cited work belongs to Herroelen and Leus (2005) where they investigated a project scheduling under uncer- tainty. The other highly cited paper was accomplished by Merkle et al. (2002) which was a meta- heuristics method named ant colony optimization for resource-constrained project scheduling. Hart- mann (2010) in his remarkable work provided a competitive genetic algorithm for resource‐con- strained project scheduling. This work is one of the well-known non-review paper which has re- ceived a high citation and the average citation per year was also the highest for this item. A close look at the highly cited works listed in Table 3 reveals that many of them were associated with meta-heuristics methods ((Boctor, 1990, 1993; Boctor, 1996; Bouleimen & Lecocq, 2003; Debels et al., 2006; Debels & Vanhoucke, 2007; Gonçalves et al., 2008; Hartmann, 1998; Hartmann, 2001; Hartmann, 2002; Józefowska et al., 2001). This can be also verified in Fig. 4 where genetic algo- rithm has been used significantly. Table 3 The summary of the most cited articles Paper Total Citations TC per Year BRUCKER P, 1999, EUR J OPER RES 952 47.6 KOLISCH R, 1997, EUR J OPER RES 692 31.4545 HERROELEN W, 2005, EUR J OPER RES 562 40.1429 MERKLE D, 2002, IEEE TRANS EVOL COMPUT 483 28.4118 KOLISCH R, 2006, EUR J OPER RES 467 35.9231 HARTMANN S, 2010, EUR J OPER RES 428 47.5556 KOLISCH R, 1996, EUR J OPER RES 422 18.3478 HARTMANN S, 1998, NAV RES LOGIST 372 17.7143 HERROELEN W, 1998, COMPUT OPER RES 359 17.0952 BOULEIMEN K, 2003, EUR J OPER RES 341 21.3125 HARTMANN S, 2000, EUR J OPER RES 327 17.2105 MUSA JD, 1975, IEEE TRANS SOFTWARE ENG 316 7.1818 DAVIS EW, 1975, MANAGE SCI 315 7.1591 KOO B, 2000, J CONSTR ENG MANAGE 301 15.8421 KOLISCH R, 2001, OMEGA 295 16.3889 TALBOT FBRIAN, 1982, MANAGE SCI 262 7.0811 PATTERSON JH, 1984, MANAGE SCI 261 7.4571 CHO SH, 2005, IEEE TRANS ENG MANAGE 241 17.2143 BAKER KR, 2009, PRINC OF SEQUENCING AND SCHEDULING 225 22.5 CHRISTOFIDES N, 1987, EUR J OPER RES 221 6.9062 DEBELS D, 2006, EUR J OPER RES 215 16.5385 JARBOUI B, 2008, APPL MATH COMPUT 213 19.3636 MINGOZZI A, 1998, MANAGE SCI 211 10.0476
  6. 170   ÖZDAMAR L, 1995, IIE TRANS 211 8.7917 BRUCKER P, 1998, EUR J OPER RES 196 9.3333 VALLS V, 2005, EUR J OPER RES 184 13.1429 HARTMANN S, 2002, NAV RES LOGIST 184 10.8235 GONÇALVES JF, 2008, EUR J OPER RES 182 16.5455 KOLISCH R, 1996, J OPER MANAGE 176 7.6522 IP WH, 2003, COMP OPER RES 173 10.8125 LI KY, 1992, EUR J OPER RES 173 6.4074 PETEGHEM VV, 2010, EUR J OPER RES 171 19 ALCARAZ J, 2001, ANN OPER RES 171 9.5 BOCTOR FF, 1990, EUR J OPER RES 171 5.8966 KURTULUS I, 1982, MANAGE SCI 171 4.6216 HARTMANN S, 2001, ANN OPER RES 170 9.4444 ZHOU X, 2007, TRANSP RES PART B METHODOL 158 13.1667 DEMEULEMEESTER EL, 1997, MANAGE SCI 157 7.1364 RODAMMER FA, 1988, IEEE TRANS SYST MAN CYBERN 154 4.9677 WGLARZ J, 2011, EUR J OPER RES 153 19.125 VALLS V, 2008, EUR J OPER RES 152 13.8182 HERROELEN W, 2004, INT J PROD RES 152 10.1333 MENDES JJM, 2009, COMP OPER RES 151 15.1 CESTA A, 2002, J HEURISTICS 151 8.8824 ALBA E, 2007, INF SCI 149 12.4167 SPRECHER A, 1998, EUR J OPER RES 148 7.0476 ZHANG H, 2005, AUTOM CONSTR 147 10.5 ADELI H, 1997, J CONSTR ENG MANAGE 146 6.6364 SPRECHER A, 1995, EUR J OPER RES 146 6.0833 DAVIS EW, 1973, AIIE TRANS 145 3.1522 KHANZODE A, 2008, ELECTRON J INF TECHNOL CONSTR 142 12.9091 DEMEULEMEESTER E, 2003, J SCHEDULING 142 8.875 ALCARAZ J, 2003, J OPER RES SOC 137 8.5625 AL-FAWZAN MA, 2005, INT J PROD ECON 133 9.5 ARTIGUES C, 2003, EUR J OPER RES 132 8.25 ÖZDAMAR L, 1999, IEEE TRANS SYST MAN CYBERN PT C APPL 128 6.4 SPRECHER A, 1997, OR SPECTRUM 128 5.8182 SAIDI-MEHRABAD M, 2007, INT J ADV MANUF TECHNOL 127 10.5833 ZHOU X, 2005, EUR J OPER RES 125 8.9286 TUKEL OI, 2006, EUR J OPER RES 124 9.5385 VAN DE VONDER S, 2005, INT J PROD ECON 124 8.8571 MORI M, 1997, EUR J OPER RES 123 5.5909 MOORTHY R, 2006, OR SPECTRUM 120 9.2308 MIKA M, 2005, EUR J OPER RES 120 8.5714 TORMOS P, 2001, ANN OPER RES 120 6.6667 KOLISCH R, 1997, IIE TRANS 118 5.3636 ZHANG H, 2006, INT J PROJ MANAGE 117 9 MÖHRING RH, 2003, MANAGE SCI 117 7.3125 LEE JK, 1996, J OPER RES SOC 115 5 LEVNER E, 2010, COMPUT IND ENG 114 12.6667 LONG LD, 2008, INT J PROJ MANAGE 114 10.3636 WANG D, 2001, IEEE TRANS SYST MAN CYBERN PT C APPL REV 113 6.2778 HERROELEN WS, 1997, EUR J OPER RES 112 5.0909 VAN DE VONDER S, 2008, EUR J OPER RES 109 9.9091 BOCTOR FF, 1993, INT J PROD RES 109 4.1923 BOCTOR FF, 1996, INT J PROD RES 108 4.6957 YANG XS, 2011, COMMUN COMPUT INFO SCI 107 13.375 BROWNING TR, 2010, INT J PROD ECON 107 11.8889 LOVA A, 2009, INT J PROD ECON 107 10.7 DREXL A, 1991, MANAGE SCI 106 3.7857 NONOBE K, 2002, OPER RES COMPUT SCI INTERFACES SER 105 6.1765 DOERSCH RH, 1977, MANAGE SCI 105 2.5 SENOUCI AB, 2001, J CONSTR ENG MANAGE 103 5.7222 DE REYCK B, 1998, EUR J OPER RES 103 4.9048 DEBELS D, 2007, OPER RES 102 8.5 JÓZEFOWSKA J, 2001, ANN OPER RES 102 5.6667 STEYN H, 2001, INT J PROJ MANAGE 102 5.6667 KATEHAKIS MN, 1987, MATH OPER RES 102 3.1875
  7. M. R. Ghaeli and S. Sadi-Nezhad / Journal of Project Management 4 (2019) 171 Fig. 4. The frequency of the keywords used in different project scheduling studies 5. Contribution of the countries One of the interesting areas of the interest is to learn more about the contribution of different coun- tries in project scheduling. As we can observe from the results of Fig. 5, researchers from China (537 papers), United States (487 papers), Iran (257 papers) and Germany (215) have contributed the most on project scheduling. Fig. 5. The frequency of the keywords used in different project scheduling studies 6. Conclusion This study has tried to provide a comprehensive review of the studies published in the literature associated with project scheduling. The study has indicated that this field has been popular mostly among researchers in United States, China, Germany and Iran. The study has also indicated that while researchers from Germany published a relatively high number of papers, they were also suc-
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